ArticleGenome research2019
Network-based hierarchical population structure analysis for large genomic data sets.
Article in Genome research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Assessing the Application of a Genomic Network Analysis in Population Ecology: Inferring Patterns of Dispersal and Geographic Structure in the Emerging Pathogen,Ecology and evolution · 2026Article
- Reflections on the Human Genome Diversity Project: a conversation with Marcus W. Feldman, Henry T. Greely, and Mary-Claire King.Genetics · 2026Article
- Evaluating inbreeding and assessing the risk of outbreeding depression in genetic rescue using whole-genome sequence data.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Comparison between SNP array and imputed data to estimate population structure and ROH hotspots in horse breeds.BMC genomics · 2025Article
- Evolutionary Influences on Local Patterns of Genetic Relatedness.bioRxiv : the preprint server for biology · 2025Article
- The multi-scale complexity of human genetic variation beyond continental groups.bioRxiv : the preprint server for biology · 2024Article
- Ancient genomics support deep divergence between Eastern and Western Mediterranean Indo-European languages.bioRxiv : the preprint server for biology · 2024Article
- A Comprehensive Analysis of 3 Moroccan Genomes Revealed Contributions From Both African and European Ancestries.Evolutionary bioinformatics online · 2024Article
- Population genomics of post-glacial western Eurasia.Nature · 2024Article
- A rarefaction approach for measuring population differences in rare and common variation.Genetics · 2023Article
- Prenatal Genetic Testing in the Era of Next Generation Sequencing: A One-Center Canadian Experience.Genes · 2022Article
- Extracting hierarchical features of cultural variation using network-based clustering.Evolutionary human sciences · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Analysis of population structure in natural populations using genetic data is a common practice in ecological and evolutionary studies. With large genomic data sets of populations now appearing more frequently across the taxonomic spectrum, it is becoming increasingly possible to reveal many hierarchical levels of structure, including fine-scale genetic clusters. To analyze these data sets, methods need to be appropriately suited to the challenges of extracting multilevel structure from whole-genome data. Here, we present a network-based approach for constructing population structure representations from genetic data. The use of community-detection algorithms from network theory generates a natural hierarchical perspective on the representation that the method produces. The method is computationally efficient, and it requires relatively few assumptions regarding the biological processes that underlie the data. We show the approach by analyzing population structure in the model plant species
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